Slovenia is a nation in Central Europe with an Adriatic Sea border. Austria, Croatia, Hungary, and Italy are nearby nations. Slovenia manages some of Europe’s main transit networks despite its tiny size. Northern Slovenia is dominated by the Alps, and the eastern region is home to many rivers. The government is a parliamentary republic, with the president serving as the head of state and the prime minister as the head of government. Slovenia features a mixed economic system in which there is flexibility for the private sector but the state is heavily involved in centralized planning. Member of the European Union is Slovenia (EU).
The sub-Mediterranean, Alpine, and continental climatic types can all be found in Slovenia. The sub-Mediterranean climate type has an average annual temperature of 12°C, ranging from 8°C to 1°C in Slovenia’s lower central areas to 0°C in its highest peaks. The country’s annual precipitation varies greatly, ranging from 800 mm in the far north-eastern and 1000 mm in the far south-western regions to over 3000 mm in the far north-western region.
## date province country lat
## Min. :2020-01-22 Length:2652 Length:2652 Min. :46.15
## 1st Qu.:2020-08-29 Class :character Class :character 1st Qu.:46.15
## Median :2021-04-07 Mode :character Mode :character Median :46.15
## Mean :2021-04-07 Mean :46.15
## 3rd Qu.:2021-11-14 3rd Qu.:46.15
## Max. :2022-06-23 Max. :46.15
## long type cases uid
## Min. :15 Length:2652 Min. :-253972.0 Min. :705
## 1st Qu.:15 Class :character 1st Qu.: 0.0 1st Qu.:705
## Median :15 Mode :character Median : 10.0 Median :705
## Mean :15 Mean : 392.2 Mean :705
## 3rd Qu.:15 3rd Qu.: 377.2 3rd Qu.:705
## Max. :15 Max. : 23332.0 Max. :705
## iso2 iso3 code3 combined_key
## Length:2652 Length:2652 Min. :705 Length:2652
## Class :character Class :character 1st Qu.:705 Class :character
## Mode :character Mode :character Median :705 Mode :character
## Mean :705
## 3rd Qu.:705
## Max. :705
## population continent_name continent_code
## Min. :2078932 Length:2652 Length:2652
## 1st Qu.:2078932 Class :character Class :character
## Median :2078932 Mode :character Mode :character
## Mean :2078932
## 3rd Qu.:2078932
## Max. :2078932
According to figure 2,Death cases increased in the latter part of 2021 where the all time high recorded is (68) and Slovania managed to take control of it and by the begining of 2022.
## [1] 540 562
Figure 3 represents Time series plot of Recovered cases which has hit an all time high of (4000) cases per day by the end of 2021.
## date province country lat long type cases uid iso2 iso3
## 1 2020-01-22 <NA> Slovenia 46.1512 14.9955 confirmed 0 705 SI SVN
## 2 2020-01-23 <NA> Slovenia 46.1512 14.9955 confirmed 0 705 SI SVN
## 3 2020-01-24 <NA> Slovenia 46.1512 14.9955 confirmed 0 705 SI SVN
## 4 2020-01-25 <NA> Slovenia 46.1512 14.9955 confirmed 0 705 SI SVN
## 5 2020-01-26 <NA> Slovenia 46.1512 14.9955 confirmed 0 705 SI SVN
## 6 2020-01-27 <NA> Slovenia 46.1512 14.9955 confirmed 0 705 SI SVN
## code3 combined_key population continent_name continent_code
## 1 705 Slovenia 2078932 Europe EU
## 2 705 Slovenia 2078932 Europe EU
## 3 705 Slovenia 2078932 Europe EU
## 4 705 Slovenia 2078932 Europe EU
## 5 705 Slovenia 2078932 Europe EU
## 6 705 Slovenia 2078932 Europe EU
## [1] 2308 2330
## integer(0)
According to figure 4 represents confirmed(red), death(green) and recovered(blue) cases ofcorona virus in Slovania. Eventhough active cases rapidly increased in the first half of 2021, death cases were not proportianal with the active cases. Medical System of Slovania managed to keep deaths under control at a time where Confirmed cases rised rapidly.
library(dplyr)
library(coronavirus)
library(ggplot2)
library(plotly)
filter_by_slovania <- coronavirus %>% filter(country == "Slovenia")
q2 <- filter_by_slovania %>% filter(type == "confirmed")
q3 <- filter_by_slovania %>% filter(type == "death")
q4 <- filter_by_slovania %>% filter(type == "recovery")
dfff <- data.frame(v1 =cumsum(q2$cases - (q3$cases + q4$cases)),date =filter_by_slovania$date)
p <- ggplot(dfff, aes(x=date, y=v1)) +geom_line() +labs(x="Year",y="Cases",title = "The plot of active corona case in Slovenia")
ggplotly(p)
countryselection<-coronavirus%>%filter(country==c("Hungary","Croatia","Italy","Slovakia","Slovenia"))
countryselection_death<- countryselection%>%filter(type =="death")
countryselection_confirmed<- countryselection%>%filter(type =="confirmed")
countryselection_recovered<- countryselection%>%filter(type =="recovery")
countryselection_recovered <- countryselection_recovered %>% mutate(cases = replace(cases, which(cases < 0), NA))
which(is.na(countryselection_recovered$cases))
## [1] 113 542 543 818
countryselection_recovered$cases[113] = mean(c(countryselection_recovered$cases[112], countryselection_recovered$cases[114]))
countryselection_recovered$cases[542] = mean(c(countryselection_recovered$cases[541], countryselection_recovered$cases[544]))
countryselection_recovered$cases[543] = mean(c(countryselection_recovered$cases[541], countryselection_recovered$cases[544]))
countryselection_recovered$cases[818] = mean(c(countryselection_recovered$cases[817], countryselection_recovered$cases[819]))
Slovenia_Hungary<-countryselection%>%filter(country==c("Slovenia","Hungary"))
Slovenia_Hungary_death<- Slovenia_Hungary%>%filter(type =="death")
ggplot(countryselection_death,aes(date, cases ,color=country),is.na=FALSE)+geom_line()
ggplot(countryselection_confirmed,aes(date, cases ,color=country),is.na=FALSE)+geom_line()
ggplot(countryselection_recovered,aes(date, cases ,color=country),is.na=FALSE)+geom_line()
ggplot(Slovenia_Hungary_death,aes(date, cases ,color=country),is.na=FALSE)+geom_line()